To recognize a face, a feature vector for identifying an individual person needs to be extracted from an image of the face. In general, a local characteristics-based method or a global characteristics-based method is used to extract a feature vector from a face image.
In the local characteristics-based method, a feature vector is extracted using the shapes and locations of and the relationship between characteristic parts (eyes, nose, mouth, etc.) of a face. In the global characteristics-based method, a feature vector is extracted using all the parts of a face. In detail, the global characteristics method includes a Principal Component Analysis (PCA) method and a Linear Discriminant Analysis (LDA) method.